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• W2517778851 abstract "Community detection is a common problem in graph data analytics. It consists of finding groups of densely connected nodes with few connections to nodes outside of the group. In particular, identifying communities in large-scale networks is an important task in many scientific domains. Community detection algorithms are used to study the structural properties of real-world networks. In this review, we evaluated some of the traditional algorithms for overlapping and disjoint community detection on large-scale real-world networks to identify the best community in realtime networks." @default.
• W2517778851 created "2016-09-16" @default.
• W2517778851 creator A5001837545 @default.
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• W2517778851 date "2016-08-31" @default.
• W2517778851 modified "2023-09-27" @default.
• W2517778851 title "Survey of Community Detection Algorithms to Identify the Best Community in Real-Time Networks" @default.
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• W2517778851 doi "https://doi.org/10.6084/m9.figshare.3795789.v1" @default.
• W2517778851 hasPublicationYear "2016" @default.
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